New maths to predict dangerous hospital epidemics

08/18/2016

Mathematicians are now developing completely new statistical calculations on the world’s fastest computers in order to be able to predict how epidemics of dangerous hospital bacteria spread. Studying the entire genomes of bacteria has now thrown open entirely new possibilities for revealing their secrets. It is this genetic knowledge that scientists use to understand bacterial epidemics.

Checking the genes of a single bacterium is not enough. The scientists have to check the genes of thousands of bacteria in order to understand what the individual genes do and how the population evolves.

The dataset quickly becomes so enormous that it is not possible to interpret by means of ordinary computing operations.

In order to reveal the secrets of the bacteria, statisticians are now developing entirely new mathematical methods for describing the evolution of bacteria, how genomes change over time, and what affects these genes.

The bacteria unfortunately have the feared ability to warn others of their kind by transferring genes to them when they are subjected to antibiotics attack. This is called horizontal gene transfer, and makes hospital bacteria even more difficult to gain control of. In other words, the bacteria can borrow genes from one another. This mechanism gives them extra resistance to antibiotics therapy.

"Normally becoming resistant to antibiotics comes at an extra evolutionary cost to bacteria. They grow more slowly and divide more inefficiently. We discovered that certain mutations in the bacteria counteract this effect, with the result that they were able both to be drug-resistant and to grow just as well. This is an enormous advantage for the bacteria, because they can spread much faster", explains Corander.

The objective of his research is to optimise treatment of patients who are infected by dangerous hospital bacteria. Many types of antibiotics have severe side effects, and must therefore only be used when absolutely necessary. Sometimes no antibiotics are effective.

"There are at least seventeen different antibiotics against tuberculosis. The treatment is normally a combination of two or three different drugs, and may take two years. We know which bacterial genes cause which drug-resistance. The gene test enables hospitals to drop antibiotics that are not efficacious."

Jukka Corander has primarily investigated how fast bacteria become drug-resistant, and where the different types of tuberculosis bacteria are to be found.

One of the studies is from a Karen refugee camp located between Burma and Thailand. There he discovered enormous variations in the antibiotic-resistant bacteria. Corander compared the genomes of 3000 bacteria, and found 20 per cent variation in the genomes of individual bacterial species. This is a huge difference. The genetic difference between humans and chimpanzees, by way of comparison, is only one per cent.

"This shows how fast bacterial evolution takes place. The bulk of the evolutionary changes are due to the fact that bacteria borrow genes from one another. They have different strategies for this borrowing. Some bacteria have an enormous capacity for borrowing genes from one another and passing the genes on to others when they are subjected to a selective pressure, such as antibiotics."

By combining knowledge of bacterial genes with which types of antibiotics were prescribed when, Jukka Corander was able to use mathematical models to calculate back in time to a year or twenty years ago. This enabled him to find out which genes the bacteria lent one another when, and to calculate which types of antibiotics led to which type of drug-resistance.

The amount of data was so enormous that the statisticians used a supercomputer running two thousand parallel computations for two full months before they got the answers. On an ordinary PC, these computations would have taken 330 years.

"In 2015 there were 100 000 bacterial genome sequences. This year the figure is one million. The amount of data is exploding. In three years, it will be a hundred times larger again, and in five to ten years perhaps a thousand times larger. We cannot rest. We do not have good enough algorithms for the future. Today’s algorithms are far too slow. In order to analyse this vast quantity of data, we must develop far faster algorithms."

The new mathematical and statistical methods are released on the internet – and will be available to everyone.

"Bacteria cause several billion infections each year. It is often the same types of bacteria that kill and disable people. Our aim is to reduce the burden of disease on ordinary people, the spreading of infection and the number of illnesses in the world", affirms Professor Jukka Corander.